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Automatic method for tracing regions of interest in rat brain magnetic resonance imaging studies
Author(s) -
Nie Binbin,
Hui Jiaojie,
Wang Lijing,
Chai Pei,
Gao Juan,
Liu Shuangquan,
Zhang Zhijun,
Shan Baoci,
Zhao Shujun
Publication year - 2010
Publication title -
journal of magnetic resonance imaging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.563
H-Index - 160
eISSN - 1522-2586
pISSN - 1053-1807
DOI - 10.1002/jmri.22283
Subject(s) - jaccard index , computer science , atlas (anatomy) , artificial intelligence , brain atlas , region of interest , pattern recognition (psychology) , tracing , computer vision , similarity (geometry) , image (mathematics) , medicine , anatomy , operating system
Purpose To automatically extract regions of interest (ROIs) and simultaneously preserve the anatomical characteristics of each individual, we developed a new atlas‐based method utilizing a pair of coregistered brain template and digital atlas. Materials and Methods Unlike the previous atlas‐based method, this method treats each individual as the target image, and the template and atlas are each transformed to register with the individual. To evaluate the accuracy of this method we implemented it in extracting the hippocampus from two groups of T 2 ‐weighted structural images with different spatial resolutions and a group of T 2 *‐weighted functional images. Furthermore, the results were compared against a manually segmented hippocampus and an atlas‐derived hippocampus. Results Jaccard similarity (JS) reached 84.7%–90.5%, and relative error in volume (RV) was 4.8%–12.7%. The consistency observed between the results of the proposed method and manual drawing was therefore considerable. Conclusion We developed a new atlas‐based method for ROI extraction that can automatically extract ROI and simultaneously preserve each individual's unique anatomical characteristics. J. Magn. Reson. Imaging 2010;32:830–835. © 2010 Wiley‐Liss, Inc.